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Building upon uncertainty reduction theory, this work aims to explore how four uncertainty reduction factors (i.e. online property review, online textual description, online visual description and online instant messenger) mitigate property quality uncertainty and property fit uncertainty, which further influence Airbnb use intention.

This work tests the proposed research model using a structural equation modeling approach with 335 Airbnb users.

The findings reveal that the online property review, online textual description, online visual description and online instant messenger can efficiently mitigate property quality uncertainty and property fit uncertainty, which ultimately influence Airbnb use intention.

This study provides useful insights on mitigating property uncertainty in the peer-to-peer (P2P) accommodation platforms. Researchers are encouraged to investigate the boundary conditions that influence the effectiveness of uncertainty reduction strategies in alleviating property uncertainty.

P2P accommodation service providers are suggested to take actionable uncertainty reduction strategies to mitigate property uncertainty in online P2P accommodation platforms.

First, this study advances research on P2P accommodation by identifying two key types of property uncertainty, namely, property quality uncertainty and property fit uncertainty. Second, this study extends research on P2P accommodation by proposing contextualized passive, active and interactive uncertainty reduction strategies in mitigating property uncertainty. Third, this study extends uncertainty reduction theory to the P2P accommodation context. Fourth, this study enriches uncertainty reduction theory by verifying the mediating effects of property quality uncertainty and property fit uncertainty.

Positive reviews can enrich the favorable impression of peer-to-peer accommodation products, and seizing this impression is vital for hosts. This study aims to focus on hosts’ response strategies to positive reviews and their effects.

This study categorizes hosts’ response strategies to positive reviews into cordial and tailoring responses. This study empirically analyzes the influence of these response strategies on subsequent review volumes using 1,283 valid listings and zero-inflation negative binomial regression models.

While hosts use cordial responses more, tailoring responses are more likely to drive subsequent reviews. In addition, when the host chooses entirely shared accommodation or sets a high price, the facilitating effect of the two response strategies on subsequent reviews weakens.

This study enriches the knowledge system on managerial responses by proposing two specific response strategies to positive reviews that can be adopted by peer-to-peer accommodation hosts and by finding the promoting impact of these strategies on subsequent review volumes.

This study recommends that peer-to-peer accommodation hosts adopt cordial and tailoring responses to encourage subsequent consumer reviewing behavior.

As an early attempt to explore hosts’ responses to positive reviews and their impacts on subsequent review volumes, this study provides valuable insights into further research on positive review response strategies in the digital space.

A trend toward higher quality has demanded more strategic investments in the transaction of coffee supply in Brazil. Instead of internalizing this transaction, one firm, illycaffè, has challenged the vertical integration assumption by adopting contracts to coordinate its supply. Aiming to investigate whether this firm is losing economic efficiency in terms of coordination, or whether it is being efficient due to a proper definition and allocation of property and decision rights, the purpose of this paper is to analyze the transaction attributes of illycaffè’s suppliers according to the vertical integration dilemma.

The research design is based on a survey of 105 coffee growers analyzed through probit regression. Using a transaction costs approach, the study empirically tests whether well-designed contracts can act as a hierarchy by following the efficient alignment hypothesis.

The results emphasize asset specificity, uncertainty and incentives as determinants for being an illycaffè supplier. In other words, these findings demonstrate that a well-designed contract can substitute a hierarchy based on transaction costs economics. It contributes by illustrating other coordination alternatives overlapping vertical integration, even in environments of high uncertainty and asset specificity, which encourages other private strategies based on allocation of property and decision rights of hybrid arrangements.

The study adopts a unique survey about transaction costs in the transactions of high-quality coffee supply in Brazil. The main contribution is to shed light on the cases where, how and why contracts can substitute the need for in-house production, and to guide private and public strategies using this background.

Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.

The purpose of this article is to investigate the relationship between cash flow uncertainty and the underpricing of real estate investment trust (REIT) initial public offerings (IPOs) using hand-collected data on income guarantee in Thailand from January 2005 to December 2019.

This article uses linear regression to determine the relationship between underpricing (initial return) and proxy for cash flow uncertainty (income guarantee), controlling for other factors. Because issuers can use several actions to signal their quality under asymmetric information, the joint decisions are analyzed as simultaneous equations and estimated using three-stage least square (3SLS) to address potential endogeneity concern.

This article finds that underpricing, on average, is negatively related to income guarantee, which is a proxy for ex ante cash flow uncertainty. The relationship is economically and statistically significant and robust to simultaneous equations estimation. Further investigation shows that REITs with income guarantee tend to have lower systematic risk (measured by CAPM beta) and returns, making the nature of some REITs more debt-like than equity-like.

For issuers, the result suggests that offering income guarantee (which is more costly for assets with lower quality) can be a useful signal of asset quality to investors and reduce IPO discount. For institutional and retail investors, the results are informative about the risk-return tradeoffs in REIT IPO investment opportunities. Income guarantees makes REIT exposure more fix income-like, so there is a need to consider the credibility of the guarantor as well.

This article is the first to use income guarantee as an ex ante measure of cash flow uncertainty and explicitly investigates its linkage to IPO underpricing. This aspect of uncertainty and IPO underpricing remains little-studied in the academic literature. It also contributes to the growing literature of REIT IPOs in Asia.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

To address formally the issue of uncertainty in valuing real estate.

Monte Carlo simulations are used to incorporate the uncertainty of valuation parameters. The probability distributions of the various parameters are constructed using empirical data and a simple model is suggested to compute the discount rate.

The central values of the simulations are in most cases slightly less than the hedonic values. The confidence intervals are found to be most sensitive to the long‐term equilibrium interest rate being used and to the expected growth rate of the terminal value.

Further research should focus on the stability of the model when other portfolios are used and for different periods of the real estate cycle. It would also be fruitful to dig deeper in the relation between capital expenses and property values.

Risk can be assessed by valuers as they can measure the probability that the value of a property be less than a given threshold.

By incorporating uncertainty, the analysis does not yield merely a point estimate of the property's value but rather the entire distribution of values. Also this paper constitutes a contribution to the debate about valuation variation and the margin of error in valuing properties.